WNC - VIS: Industrials Dashboard For December

2023-12-17 05:46:50 ET

Summary

• Industrials are the second most overvalued sector behind technology.
• Nevertheless, the transportation industry shows good value and quality scores.
• VIS, an alternative to XLI.
• 10 industrial stocks cheaper than their peers in December 2023.

This monthly article series shows a dashboard with aggregate subsector metrics in industrials. It is also a review of sector ETFs like Industrial Select Sector SPDR ETF ( XLI ), Fidelity MSCI Industrials Index ETF ( FIDU ) and Vanguard Industrials ETF ( VIS ), whose largest holdings are used to calculate these metrics.

Shortcut

The next two paragraphs in italic describe the dashboard methodology. They are necessary for new readers to understand the metrics. If you are used to this series or if you are short of time, you can skip them and go to the charts.

Base Metrics

I calculate the median value of five fundamental ratios for each subsector : Earnings Yield ("EY"), Sales Yield ("SY"), Free Cash Flow Yield ("FY"), Return on Equity ("ROE"), Gross Margin ("GM"). The reference universe includes large companies in the U.S. stock market. The five base metrics are calculated on trailing 12 months. For all of them, higher is better. EY, SY and FY are medians of the inverse of Price/Earnings, Price/Sales and Price/Free Cash Flow. They are better for statistical studies than price-to-something ratios, which are unusable or non-available when the "something" is close to zero or negative (for example, companies with negative earnings). I also look at two momentum metrics for each group: the median monthly return (RetM) and the median annual return (RetY).

I prefer medians to averages because a median splits a set in a good half and a bad half. A capital-weighted average is skewed by extreme values and the largest companies. My metrics are designed for stock-picking rather than index investing.

Value and Quality Scores

I calculate historical baselines for all metrics. They are noted respectively EYh, SYh, FYh, ROEh, GMh, and they are calculated as the averages on a look-back period of 11 years. For example, the value of EYh for transportation in the table below is the 11-year average of the median Earnings Yield in transportation companies. The Value Score ("VS") is defined as the average difference in % between the three valuation ratios (EY, SY, FY) and their baselines (EYh, SYh, FYh). The same way, the Quality Score ("QS") is the average difference between the two quality ratios (ROE, GM) and their baselines (ROEh, GMh).

The scores are in percentage points. VS may be interpreted as the percentage of undervaluation or overvaluation relative to the baseline (positive is good, negative is bad). This interpretation must be taken with caution: the baseline is an arbitrary reference, not a supposed fair value. The formula assumes that the three valuation metrics are of equal importance.

Current Data

The next table shows the metrics and scores as of last week's closing. Columns stand for all the data named and defined above.

Value and Quality Chart

The next chart plots the Value and Quality Scores by subsector (higher is better).

Evolution Since Last Month

The value score has deteriorated in all subsectors, mostly due to price action.

Momentum

The next chart plots momentum data.

Interpretation

Industrials are overvalued by about 22% relative to 11-year averages according to my S&P 500 monthly dashboard . This is the second most overvalued GICS sector behind information technology. Nevertheless, the transportation industry is undervalued by about 10% using the same metrics, and it shows a quality score close to the historical baseline. Other subsectors are overvalued by 14% to 32%. Overvaluation may be partly justified by a good quality score for building/construction/electric equipment, and to a lesser extent for services/distribution. Aerospace/defense is the less attractive subsector, with both value and quality scores significantly below the baseline.

Focus on VIS

Vanguard Industrials ETF ( VIS ) has been tracking the MSCI US IMI Industrials 25/50 Index since 09/23/2004. It has a total expense ratio of 0.10%, the same as XLI, and marginally more expensive than FIDU (0.08%). The same portfolio is available through a mutual fund (VINAX).

As of writing, the fund has 393 holdings. The next table lists the top 10 names with some fundamental ratios. They represent 27.5% of asset value and the heaviest names weigh about 3%. Therefore, the portfolio is well-diversified and risks related to individual companies are moderate.

The heaviest industry in the portfolio is aerospace/defense (16.2%). VIS has much more holdings than XLI (393 large to small caps vs. 80 large and mid caps). However, their return and risk metrics since VIS inception are almost identical, as reported below.

In summary, VIS is a well-diversified fund with cheap management fees for investors seeking capital-weighted exposure in industrials. VIS and XLI are equivalents for buy-and-hold investors. However, higher trading volumes make XLI a better instrument for traders and tactical allocation strategies. Investors looking for a more balanced portfolio may prefer the Invesco S&P 500 Equal Weight Industrials ETF ( RSPN ).

Dashboard List

I use the first table to calculate value and quality scores. It may also be used in a stock-picking process to check how companies stand among their peers. For example, the EY column tells us that a transportation company with an Earnings Yield above 0.0507 (or price/earnings below 19.72) is in the better half of the subsector regarding this metric. A Dashboard List is sent every month to Quantitative Risk & Value subscribers with the most profitable companies standing in the better half among their peers regarding the three valuation metrics at the same time. The list below was sent to subscribers several weeks ago based on data available at this time.

It is a rotational model with a statistical bias toward excess returns on the long-term, not the result of an analysis of each stock.

For further details see: